| SSlogis {stats} | R Documentation |
This selfStart model evaluates the logistic
function and its gradient. It has an initial attribute that
creates initial estimates of the parameters Asym,
xmid, and scal.
SSlogis(input, Asym, xmid, scal)
input |
a numeric vector of values at which to evaluate the model. |
Asym |
a numeric parameter representing the asymptote. |
xmid |
a numeric parameter representing the x value at the
inflection point of the curve. The value of SSlogis will be
Asym/2 at xmid. |
scal |
a numeric scale parameter on the input axis. |
a numeric vector of the same length as input. It is the value of
the expression Asym/(1+exp((xmid-input)/scal)). If all of
the arguments Asym, xmid, and scal are
names of objects the gradient matrix with respect to these names is attached as
an attribute named gradient.
Jose Pinheiro and Douglas Bates
data( ChickWeight ) Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ] SSlogis( Chick.1$Time, 368, 14, 6 ) # response only Asym <- 368; xmid <- 14; scal <- 6 SSlogis( Chick.1$Time, Asym, xmid, scal ) # response and gradient getInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1) ## Initial values are in fact the converged values fm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1) summary(fm1)